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Université de Fribourg

Heterogenous scaling in the inter-event time of on-line bookmarking

Wang, Peng ; Xie, Xiao-Yi ; Yeung, Chi Ho ; Wang, Bing-Hong

In: Physica A: Statistical Mechanics and its Applications, 2011, vol. 390, no. 12, p. 2395-2400

In this paper, we study the statistical properties of bookmarking behaviors in We find that the inter-event time (τ) distributions of bookmarking decay in a power-like manner as τ increases at both individual and population levels. Remarkably, we observe a significant change in the exponent when the inter-event time increases from the intra-day range to the inter-day range. In...

Université de Fribourg

Heterogenous human dynamics in intra- and inter-day time scales

Wang, Peng ; Lei, T. ; Yeung, Chi-Ho ; Wang, Bing-Hong

In: Europhysics Letters, 2011, vol. 94, no. 1, p. 18005

In this paper, we study two large data sets containing the information of two different human behaviors: blog-posting and wiki-revising. In both cases, the interevent time distributions decay as power laws at both individual and population level. Unlike previous studies, we put emphasis on time scales and obtain heterogeneous decay exponents in the intra- and inter-day range for the same dataset....

Université de Fribourg

Interest-driven model for human dynamics

Shang, Ming-Sheng ; Chen, Guan-Xiong ; Dai, Shuang-Xing ; Wang, Bing-Hong ; Zhou, Tao

In: Chinese Physics Letters, 2010, vol. 27, no. 4, p. 048701

Empirical observations indicate that the interevent time distribution of human actions exhibits heavy-tailed features. The queuing model based on task priorities is to some extent successful in explaining the origin of such heavy tails, however, it cannot explain all the temporal statistics of human behavior especially for the daily entertainments. We propose an interest-driven model, which can...

Université de Fribourg

Improved collaborative filtering algorithm via information transformation

Liu, Jian-Guo ; Wang, Bing-Hong ; Guo, Qiang

In: International Journal of Modern Physics C, 2009, vol. 20, no. 2, p. 285-293

In this paper, we propose a spreading activation approach for collaborative filtering (SA-CF). By using the opinion spreading process, the similarity between any users can be obtained. The algorithm has remarkably higher accuracy than the standard collaborative filtering using the Pearson correlation. Furthermore, we introduce a free parameter β to regulate the contributions of objects to...

Université de Fribourg

Effects of user's tastes on personalized recommendation

Liu, Jian-Guo ; Zhou, Tao ; Wang, Bing-Hong ; Zhang, Yi-Cheng ; Guo, Qiang

In: International Journal of Modern Physics C, 2009, vol. 20, no. 12, p. 1925-1932

In this paper, based on a weighted projection of the user-object bipartite network, we study the effects of user tastes on the mass-diffusion-based personalized recommendation algorithm, where a user's tastes or interests are defined by the average degree of the objects he has collected. We argue that the initial recommendation power located on the objects should be determined by both of their...

Université de Fribourg

Effects of high-order correlations on personalized recommendations for bipartite networks

Liu, Jian-Guo ; Zhou, Tao ; Che, Hong-An ; Wang, Bing-Hong ; Zhang, Yi-Cheng

In: Physica A, 2010, vol. 389, no. 4, p. 881-886

In this paper, we introduce a modified collaborative filtering (MCF) algorithm, which has remarkably higher accuracy than the standard collaborative filtering. In the MCF, instead of the cosine similarity index, the user–user correlations are obtained by a diffusion process. Furthermore, by considering the second-order correlations, we design an effective algorithm that depresses the influence...

Université de Fribourg

Accurate and diverse recommendations via eliminating redundant correlations

Zhou, Tao ; Su, Ri-Qi ; Liu, Run-Ran ; Jiang, Luo-Luo ; Wang, Bing-Hong ; Zhang, Yi-Cheng

In: New Journal of Physics, 2009, vol. 11, p. 123008

In this paper, based on a weighted projection of a bipartite user-object network, we introduce a personalized recommendation algorithm, called network-based inference (NBI), which has higher accuracy than the classical algorithm, namely collaborative filtering. In NBI, the correlation resulting from a specific attribute may be repeatedly counted in the cumulative recommendations from different...

Université de Fribourg

Reducing the heterogeneity of payoffs: an effective way to promote cooperation in the prisoner's dilemma game

Jiang, Luo-Luo ; Zhao, Ming ; Yang, Han-Xin ; Wakeling, Joseph Rushton ; Wang, Bing-Hong ; Zhou, Tao

In: Physical Review E, 2009, vol. 80, p. 031144

In this paper, the accumulated payoff of each agent is regulated so as to reduce the heterogeneity of the distribution of all such payoffs. It is found that there exists an optimal regulation strength at which cooperation in the prisoner's dilemma game is optimally promoted. If the heterogeneity is regulated to be either too weak or too strong, the promotive effect disappears and the evolution of...

Université de Fribourg

Emergence of target waves in paced populations of cyclically competing species

Jiang, Luo-Luo ; Zhou, Tao ; Perc, Matjaž ; Huang, Xin ; Wang, Bing-Hong

In: New Journal of Physics, 2009, vol. 11, p. 103001

We investigate the emergence of target waves in a cyclic predator–prey model incorporating a periodic current of the three competing species in a small area situated at the center of a square lattice. The periodic current acts as a pacemaker, trying to impose its rhythm on the overall spatiotemporal evolution of the three species. We show that the pacemaker is able to nucleate target waves that...

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